import pandas as pd
import plotly.graph_objects as go #has more control, customizable
import plotly.io as pio #produce an html file
import plotly.express as px #fast, low effort
import matplotlib.pyplot as plt
import yfinance as yf

start_date = '2021-01-01'
end_date = '2023-01-01'

# Set the ticker
ticker = 'AAPL'

# Get the data
data = yf.download(ticker, start_date, end_date)

data["Date"] = data.index

data = data[["Date", "Open", "High", "Low", "Close", "Adj Close", "Volume"]]

data.reset_index(drop=True, inplace=True)

[*********************100%***********************]  1 of 1 completed

data.head()

	Date	Open	High	Low	Close	Adj Close	Volume
0	2021-01-04	133.520004	133.610001	126.760002	129.410004	127.874954	143301900
1	2021-01-05	128.889999	131.740005	128.429993	131.009995	129.455978	97664900
2	2021-01-06	127.720001	131.050003	126.379997	126.599998	125.098267	155088000
3	2021-01-07	128.360001	131.630005	127.860001	130.919998	129.367020	109578200
4	2021-01-08	132.429993	132.630005	130.229996	132.050003	130.483612	105158200

# Create 20 days simple moving average column
data['20_SMA'] = data["Adj Close"].rolling(20).mean()
# Create 50 days simple moving average column
data['50_SMA'] = data["Adj Close"].rolling(50).mean()

<ipython-input-4-67c785842c60>:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['20_SMA'] = data["Adj Close"].rolling(20).mean()
<ipython-input-4-67c785842c60>:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['50_SMA'] = data["Adj Close"].rolling(50).mean()

data.head()

	Date	Open	High	Low	Close	Adj Close	Volume	20_SMA	50_SMA
0	2021-01-04	133.520004	133.610001	126.760002	129.410004	127.874954	143301900	NaN	NaN
1	2021-01-05	128.889999	131.740005	128.429993	131.009995	129.455978	97664900	NaN	NaN
2	2021-01-06	127.720001	131.050003	126.379997	126.599998	125.098267	155088000	NaN	NaN
3	2021-01-07	128.360001	131.630005	127.860001	130.919998	129.367020	109578200	NaN	NaN
4	2021-01-08	132.429993	132.630005	130.229996	132.050003	130.483612	105158200	NaN	NaN

AAPL = go.Figure(data=[go.Candlestick(x=data['Date'],open=data['Open'],high=data['High'],low=data['Low'],close=data['Close'])])

AAPL.update_layout(title='AAPL Stock Prices From 2021 to 2023', yaxis_title='USD',xaxis_title='Time')

AAPL.add_trace(go.Scatter(x=data['Date'], y=data["20_SMA"],mode='lines',name='20_SMA',line_color='blue'))

AAPL.add_trace(go.Scatter(x=data['Date'], y=data["50_SMA"],mode='lines',name='50_SMA',line_color='orange'))

AAPL.show()

plt.rcParams['figure.figsize'] = (20,10)
plt.style.use('fivethirtyeight')

Mean Reversion - Williams %R Indicator

def get_wr(high, low, close, lookback):
    highh = high.rolling(lookback).max() 
    lowl = low.rolling(lookback).min()
    wr = -100 * ((highh - close) / (highh - lowl))
    return wr

data['wr_14'] = get_wr(data['High'], data['Low'],data['Adj Close'], 14)
data = data.dropna()

<ipython-input-8-a41dcb614c67>:7: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

data.head()

	Date	Open	High	Low	Close	Adj Close	Volume	20_SMA	50_SMA	wr_14
49	2021-03-16	125.699997	127.220001	124.720001	125.570000	124.265907	115227900	122.533094	128.426685	-35.604262
50	2021-03-17	124.050003	125.860001	122.339996	124.760002	123.464325	111932600	122.232251	128.338472	-42.011794
51	2021-03-18	122.879997	123.180000	120.320000	120.529999	119.278244	121229700	121.778017	128.134917	-75.473666
52	2021-03-19	119.900002	121.430000	119.680000	119.989998	118.743843	185549500	121.289147	128.007829	-79.745455
53	2021-03-22	120.330002	123.870003	120.260002	123.389999	122.108566	111912300	121.160003	127.862660	-46.425376

ax1 = plt.subplot2grid((11,1), (0,0), rowspan = 5, colspan = 1)
ax2 = plt.subplot2grid((11,1), (6,0), rowspan = 5, colspan = 1)
ax1.plot(data['Date'],data['Adj Close'], linewidth = 2)
# ax1.plot(aapl_50, linewidth = 2,color='red')
ax1.set_title('AAPL CLOSING PRICE')
ax1.plot(data['Date'],data['20_SMA'], linewidth = 2,color='red')
ax1.plot(data['Date'],data['50_SMA'], linewidth = 2,color='orange')
ax2.plot(data['Date'],data['wr_14'], color = 'orange', linewidth = 2)
ax2.axhline(-20, linewidth = 1.5, linestyle = '--', color = 'grey')
ax2.axhline(-80, linewidth = 1.5, linestyle = '--', color = 'grey')
ax2.set_title('AAPL WILLIAMS %R 14')
plt.show()